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Predictive PAC Learning and Process Decompositions
We informally call a stochastic process learnable if it admits a generalization error approaching zero in probability for any concept class with finite VC-dimension (IID processes are the simplest example). A mixture of learnable processes need not be learnable itself, and certainly its generalizati...
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| Published in: | Adv Neural Inf Process Syst |
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| Main Authors: | , |
| Format: | Artigo |
| Language: | Inglês |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4551412/ https://ncbi.nlm.nih.gov/pubmed/26321855 |
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